[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-seo-140586-105":3,"detail-sidebar-cat-0-en-105":76,"doc-detail-140586-en":125},{"code":4,"msg":5,"data":6},0,"ok",{"site_id":7,"language":8,"slug":9,"title":10,"keywords":11,"description":12,"schema_data":13,"social_meta":69,"head_meta":71,"extra_data":73,"updated_unix":75},105,"en","coding-depression-in-the-digital-realm-an-analysis-via-systemic-functional-linguistics-and-social-semiotics","Coding Depression in the Digital Realm - An Analysis via Systemic Functional Linguistics and Social Semiotics","","This study investigates how Turkish Twitter users encode emotional states through the hashtag #depresyondayım (“I am depressed”), applying Martin and White’s (2005) Appraisal Framework within Halliday’s (1978) social semiotic perspective. Systemic Functional Linguistics is used to examine how users mobilize attitudinal resources, engagement strategies, and graduation procedures to express emotional pain, negotiate social roles, and construct identities. Qualitative analysis of 130 tweets shows a dominance of affect resources (81.5%), monoglossic engagement (84.6%), and force-based graduation (67.7%), with patterns mapped to seven thematic categories. The findings demonstrate how depression discourse functions as a versatile semiotic resource for diverse social purposes beyond clinical distress expression.",{"@graph":14,"@context":68},[15,34,51],{"@type":16,"itemListElement":17},"BreadcrumbList",[18,23,27,31],{"item":19,"name":20,"@type":21,"position":22},"https://docshare.wps.com","Home","ListItem",1,{"item":24,"name":25,"@type":21,"position":26},"https://docshare.wps.com/document/","Document",2,{"item":28,"name":29,"@type":21,"position":30},"https://docshare.wps.com/document/research-report/","Research & Report",3,{"item":32,"name":10,"@type":21,"position":33},"https://docshare.wps.com/document/coding-depression-in-the-digital-realm-an-analysis-via-systemic-functional-linguistics-and-social-semiotics/140586/",4,{"url":32,"name":10,"@type":35,"author":36,"headline":10,"publisher":39,"fileFormat":42,"inLanguage":8,"description":12,"dateModified":43,"datePublished":44,"encodingFormat":42,"isAccessibleForFree":45,"interactionStatistic":46},"DigitalDocument",{"name":37,"@type":38},"Seraphina","Person",{"url":19,"name":40,"@type":41},"DocShare","Organization","application/pdf","2026-09-11","2026-08-24",true,{"@type":47,"interactionType":48,"userInteractionCount":50},"InteractionCounter",{"@type":49},"ViewAction",5,{"@type":52,"mainEntity":53},"FAQPage",[54,60,64],{"name":55,"@type":56,"acceptedAnswer":57},"What theoretical tools does the study use to analyze #depresyondayım tweets?","Question",{"text":58,"@type":59},"It uses Halliday’s social semiotic perspective and Martin and White’s (2005) Appraisal Framework, with Systemic Functional Linguistics to model attitudinal, engagement, and graduation resources.","Answer",{"name":61,"@type":56,"acceptedAnswer":62},"How many tweets are analyzed and what is the main distribution of linguistic resources?",{"text":63,"@type":59},"The qualitative analysis covers 130 tweets. Affect resources dominate (81.5%), monoglossic engagement is most frequent (84.6%), and force-based graduation is prominent (67.7%).",{"name":65,"@type":56,"acceptedAnswer":66},"Which thematic categories structure the observed linguistic patterns?",{"text":67,"@type":59},"The analysis groups patterns into seven categories: everyday frustrations, economic hardships, emotional isolation, academic/work stress, seasonal effects, societal issues, and social deprivation.","https://schema.org",{"og:url":32,"og:type":70,"og:title":10,"og:site_name":40,"og:description":12},"article",{"robots":72,"canonical":32},"index,follow",{"doc_id":74,"site_id":7},140586,1787583139,{"code":4,"msg":77,"data":78},"success",[79,83,87,91,95,100,105,109,114,117,121],{"id":22,"doc_module":4,"doc_module_name":25,"category_name":80,"show_sort_weight":81,"slug":82},"Story & Novel",90,"story-novel",{"id":26,"doc_module":4,"doc_module_name":25,"category_name":84,"show_sort_weight":85,"slug":86},"Literature",80,"literature",{"id":33,"doc_module":4,"doc_module_name":25,"category_name":88,"show_sort_weight":89,"slug":90},"Exam",70,"exam",{"id":50,"doc_module":4,"doc_module_name":25,"category_name":92,"show_sort_weight":93,"slug":94},"Comic",60,"comic",{"id":96,"doc_module":4,"doc_module_name":25,"category_name":97,"show_sort_weight":98,"slug":99},6,"Technology",50,"technology",{"id":101,"doc_module":4,"doc_module_name":25,"category_name":102,"show_sort_weight":103,"slug":104},7,"Healthcare",40,"healthcare",{"id":106,"doc_module":4,"doc_module_name":25,"category_name":29,"show_sort_weight":107,"slug":108},8,30,"research-report",{"id":110,"doc_module":4,"doc_module_name":25,"category_name":111,"show_sort_weight":112,"slug":113},9,"Religion & Spirituality",20,"religion-spirituality",{"id":112,"doc_module":4,"doc_module_name":25,"category_name":115,"show_sort_weight":112,"slug":116},"World Cup","world-cup",{"id":118,"doc_module":4,"doc_module_name":25,"category_name":119,"show_sort_weight":118,"slug":120},10,"Lifestyle","lifestyle",{"id":122,"doc_module":4,"doc_module_name":25,"category_name":123,"show_sort_weight":50,"slug":124},19,"General","general",{"code":4,"msg":77,"data":126},{"doc_id":74,"user_id":127,"nickname":37,"user_avatar":128,"doc_module":4,"category_id":106,"category_name":29,"doc_title":10,"doc_description":12,"doc_content":129,"file_id":130,"file_url":131,"file_type":132,"file_size":133,"view_count":50,"is_deleted":4,"is_public":22,"is_downloadable":22,"audit_status":22,"page_count":134,"language":135,"language_code":8,"site_id":7,"html_lang":8,"table_of_contents":136,"faqs":137,"seo_title":138,"seo_description":12,"update_tm":75,"read_time":139},962075114101,"https://ap-avatar.wpscdn.com/avatar/e000253a75eb197efd?x-image-process=image/resize,m_fixed,w_180,h_180&k=1780044092746381165","Coding Depression in the Digital Realm: An Analysis via Systemic Functional Linguistics and Social Semiotics  \nFırat Başbuğ 1  \nBaşbuğ, F.,(2024) . Coding Depression in the Digital Realm: An Analysis via Systemic Functional Linguistics  \nand Social Semiotics. Nesne, 12(34), 497-542. DOI: 10.7816/nesne-12-34-03  \nKeywords:  \nAppraisal Framework, Systemic Functional Linguistics, social media discourse, hashtags, linguistic identity, attitude, affect, engagement  \nAnahtar Kelimeler:  \nDeğerlendirme Kuramı, Dizgeci İşlevsel Dilbilim, sosyal medyasöylemi, etiketler, dilsel kimlik, tutum, duygulanım, bağıntılaşım  \nAbstract  \nThis study investigates the language encoding of emotional states by Turkish Twitter users through the hashtag \\#depresyondayım (\"I am depressed\"), utilizing Martin and White's (2005) Appraisal Framework within Halliday's (1978) Social Semiotic perspective. This research utilizes Systemic Functional Linguistics to examine how users employ attitudinal resources, engagement methods, and graduation procedures as semiotic tools to articulate emotional pain, negotiate social roles, and create identities in digital environments. A qualitative analysis of 130 tweets indicates that the content primarily consists of affect resources (81.5%), monoglossic engagement (84.6%), and force-based graduation (67.7%) . Notable linguistic patterns were identified across seven thematic categories: everyday frustrations, economic hardships, emotional isolation, academic/work stress, seasonal effects, societal issues, and social deprivation. The research illustrates how the Appraisal Framework elucidates the intricate relationship among emotion, evaluation, and intensification in digital communication, while exposing how depression discourse operates as a multifaceted semiotic resource fulfilling diverse social functions beyond the expression of clinical distress. This study aims to contribute to digital discourse analysis by applying the Appraisal Framework to Turkish social media texts. In the process, observations were made about the role of Turkish morphological and syntactic features in evaluative language use.  \nDijital Alanda Depresyonun Kodlanması: Dizgeci İşlevsel Dilbilim ve Sosyal Göstergebilim Perspektifiyle Bir Analiz  \nÖz  \nBu çalışma, Türk Twitter kullanıcılarının \\#depresyondayım etiketi aracılığıyla duygusal durumlarını dilsel olarak nasıl kodladıklarını Halliday'in (1978) Sosyal Göstergebilim perspektifinde Martin ve White'ın (2005) Değerlendirme Kuramını kullanarak incelemektedir. Dizgeci İşlevsel Dilbilime dayanan bu araştırma, kullanıcıların duygusal durumlarını ifade etmek, sosyal konumlarını tartışmak ve dijital alanda kimliklerini inşa etmek için tutum kaynaklarını, etkileşim stratejilerini ve derecelendirme tekniklerini göstergebilimsel kaynaklar olarak nasılkullandıklarını araştırmaktadır. Bulgular, 130 tweetin nitel analiz yoluyla, tweetlerin ağırlıklı olarak duygulanım kaynakları (%81,5), tekdilli bağıntılaşım (%84,6) ve güç-temelli derecelendirme (%67,7) içerdiğini ve başta günlük hayal kırıklıkları, ekonomik zorluklar, duygusal izolasyon, akademik/iş stresi, mevsimsel etkiler, toplumsal sorunlar ve sosyal yoksunluk olmak üzere yedi tematik kategoride farklı dil örüntülerinin ortaya çıktığını göstermektedir. Araştırma, Değerlendirme Kuramının dijital iletişimde duygulanım, değerlendirme ve yoğunlaşma arasındaki karmaşık etkileşimi nasıl etkili bir şekilde aydınlattığını gösterirken, depresyon söyleminin ruhsal sıkıntıyı ifade etmenin ötesinde çeşitli sosyal amaçlara hizmet eden değerli bir göstergebilimsel kaynak olarak nasıl işlevgördüğünü ortaya koymaktadır. Bu çalışma, Değerlendirme Kuramını, Türkçe sosyal medya metinlerineuygulayarak dijital söylem analizine katkıda bulunmayı amaçlamaktadır. Bu süreçte ayrıca, Türkçenin  \nbiçimbilimsel ve sözdizimsel özelliklerinin değerlendirici dil kullanımındaki rolü hakkında gözlemler yapılmıştır.  \nMakale Bilgisi  \nGeliş tarihi: 3 Haziran 2024  \nDüzeltme tarihi: ","cbCaicy7GqiSOwEI","https://ap.wps.com/l/cbCaicy7GqiSOwEI","pdf",1024054,46,"English","# Abstract\n## Theoretical framework and method\n## Findings and thematic categories\n## Implications for digital discourse analysis","[{\"question\":\"What theoretical tools does the study use to analyze #depresyondayım tweets?\",\"answer\":\"It uses Halliday’s social semiotic perspective and Martin and White’s (2005) Appraisal Framework, with Systemic Functional Linguistics to model attitudinal, engagement, and graduation resources.\"},{\"question\":\"How many tweets are analyzed and what is the main distribution of linguistic resources?\",\"answer\":\"The qualitative analysis covers 130 tweets. Affect resources dominate (81.5%), monoglossic engagement is most frequent (84.6%), and force-based graduation is prominent (67.7%).\"},{\"question\":\"Which thematic categories structure the observed linguistic patterns?\",\"answer\":\"The analysis groups patterns into seven categories: everyday frustrations, economic hardships, emotional isolation, academic/work stress, seasonal effects, societal issues, and social deprivation.\"}]","Coding Depression in the Digital Realm - An Analysis via Systemic Functional Linguistics and Social Semiotics | PDF",116]